IDEAS home Printed from https://ideas.repec.org/p/usg/dp2007/2007-32.html
   My bibliography  Save this paper

Regression discontinuity design with covariates

Author

Listed:
  • Markus Frölich

    ()

Abstract

In this paper, the regression discontinuity design (RDD) is generalized to account for differences in observed covariates X in a fully nonparametric way. It is shown that the treatment effect can be estimated at the rate for one-dimensional nonparametric regression irrespective of the dimension of X. It thus extends the analysis of Hahn, Todd and van der Klaauw (2001) and Porter (2003), who examined identification and estimation without covariates, requiring assumptions that may often be too strong in applications. In many applications, individuals to the left and right of the threshold differ in observed characteristics. Houses may be constructed in different ways across school attendance district boundaries. Firms may differ around a threshold that implies certain legal changes, etc. Accounting for these differences in covariates is important to reduce bias. In addition, accounting for covariates may also reduces variance. Finally, estimation of quantile treatment effects (QTE) is also considered.

Suggested Citation

  • Markus Frölich, 2007. "Regression discontinuity design with covariates," University of St. Gallen Department of Economics working paper series 2007 2007-32, Department of Economics, University of St. Gallen.
  • Handle: RePEc:usg:dp2007:2007-32
    as

    Download full text from publisher

    File URL: http://ux-tauri.unisg.ch/RePEc/usg/dp2007/DP-32-Fr.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Sandra E. Black, 1999. "Do Better Schools Matter? Parental Valuation of Elementary Education," The Quarterly Journal of Economics, Oxford University Press, vol. 114(2), pages 577-599.
    2. Patrick Puhani & Andrea Weber, 2007. "Does the early bird catch the worm?," Empirical Economics, Springer, vol. 32(2), pages 359-386, May.
    3. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-475, March.
    4. Wilbert van der Klaauw, 2002. "Estimating the Effect of Financial Aid Offers on College Enrollment: A Regression-Discontinuity Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 43(4), pages 1249-1287, November.
    5. Hahn, Jinyong & Todd, Petra & Van der Klaauw, Wilbert, 2001. "Identification and Estimation of Treatment Effects with a Regression-Discontinuity Design," Econometrica, Econometric Society, vol. 69(1), pages 201-209, January.
    6. Lalive, Rafael, 2008. "How do extended benefits affect unemployment duration A regression discontinuity approach," Journal of Econometrics, Elsevier, vol. 142(2), pages 785-806, February.
    7. Joshua D. Angrist & Victor Lavy, 1999. "Using Maimonides' Rule to Estimate the Effect of Class Size on Scholastic Achievement," The Quarterly Journal of Economics, Oxford University Press, vol. 114(2), pages 533-575.
    8. Erich Battistin & Enrico Rettore, 2002. "Testing for programme effects in a regression discontinuity design with imperfect compliance," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 165(1), pages 39-57.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Frandsen, Brigham R. & Frölich, Markus & Melly, Blaise, 2012. "Quantile treatment effects in the regression discontinuity design," Journal of Econometrics, Elsevier, vol. 168(2), pages 382-395.
    2. Bartalotti, Otávio C. & Calhoun, Gray & He, Yang, 2016. "Bootstrap Confidence Intervals for Sharp Regression Discontinuity Designs with the Uniform Kernel," ISU General Staff Papers 201605010700001003, Iowa State University, Department of Economics.
    3. Tohari, Achmad & Parsons, Christopher & Rammohan, Anu, 2017. "Does Information Empower the Poor? Evidence from Indonesia's Social Security Card," IZA Discussion Papers 11137, Institute for the Study of Labor (IZA).
    4. repec:eee:wdevel:v:103:y:2018:i:c:p:100-118 is not listed on IDEAS
    5. Achmad Tohari & Christopher Parsons & Anu Rammohan, 2017. "Does Information Empower the Poor? Evidence from Indonesia’s Social Security Card," Working Papers id:12241, eSocialSciences.
    6. Ciani, Emanuele, 2016. "Retirement, pension eligibility and home production," Labour Economics, Elsevier, vol. 38(C), pages 106-120.
    7. Bergolo, Marcelo & Galván, Estefanía, 2018. "Intra-household Behavioral Responses to Cash Transfer Programs. Evidence from a Regression Discontinuity Design," World Development, Elsevier, vol. 103(C), pages 100-118.
    8. Esfandiar Maasoumi & Le Wang, 2013. "The Gender Earnings Gap: Measurement and Analysis," Emory Economics 1305, Department of Economics, Emory University (Atlanta).

    More about this item

    Keywords

    Treatment effect; causal effect; complier; LATE; nonparametric regression; endogeneity;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:usg:dp2007:2007-32. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Joerg Baumberger). General contact details of provider: http://edirc.repec.org/data/vwasgch.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.